Although uptake of combination antiretroviral therapy (cART) in people who inject drugs (PWID) infected with HIV has increased dramatically in the past decade, poor health outcomes including non-AIDS-related comorbidity and mortality in HIV-infected PWID on cART remains a significant public health problem. A crucial knowledge gap is a lack of the understanding about how injection drug use (IDU) impacts the course of HIV disease. Differences in gene regulation affected by IDU and non-adherence to cART are likely to affect the pharmacokinetics and pharmacodynamics of these treatments that may result in poor outcomes. Thus, there is an urgent need to identify genomic signatures for PWID and to link PWID-associated genomic signals to HIV outcomes in the context of cART exposure (i.e., levels in plasma). Our overall hypothesis is that PWID accrue DNA methylation (DNAm) and transcriptome variations that impact on health outcomes, and which may be explained in part by variability in cART exposure. This hypothesis is built on our previous findings showing that IDU significantly altered the blood DNA methylome in HIV-infected individuals. Furthermore, DNAm signatures associated with IDU differentiated less and greater HIV disease frailty. To test this hypothesis, our approach will first perform epigenome-wide DNAm association analysis and transcriptome-wide association analysis in HIV-infected PWID as compared to HIV-infected non-PWID who are treated with cART in two independent cohorts. Second, we will test the relationship between PWID-associated differentially methylated positions (DMP) or regions (DMR) and differential gene expression (DGE) on cART variability in plasma and also their relationships with HIV frailty and mortality. Last, we propose to integrate genetic variation (single nucleotide polymorphism [SNP]), DNAm, and gene expression that differs by HIV-infected PWID/non-PWID status. Our goal is to identify DMP or DMR and DGE between HIV-infected PWID and non-PWID in the context of cART and to apply epigenetic and transcriptomic signatures as biomarkers to predict HIV frailty and mortality. The application proposes the first integrative pharmacogenomic approach of genetic variants, epigenomic and transcriptomic associations for HIV-infected PWID in the context of cART. We expect to identify PWID- associated genes that can predict HIV cART treatment outcomes. The predictive model resulting from this project can inform biomarker identification for HIV outcomes. The proposal is the first step towards the understanding of pharmacogenomics and pharamcoepigenomics in PWID with HIV infection. The results will fill the knowledge gap of the biological basis of IDU effects on HIV outcomes and provide evidence to prioritize genes for future research of their functions in HIV progression.